CN116468521A

CN116468521A - Method, device, equipment and storage medium for optimizing goods picking of goods picking personnel

Info

Publication number: CN116468521A
Application number: CN202310444772.3A
Authority: CN
Inventors: 刘刚; 张艳薇; 耿大鹏
Original assignee: Hongxun Supply Chain Technology Co ltd
Current assignee: Hongxun Supply Chain Technology Co ltd
Priority date: 2023-04-23
Filing date: 2023-04-23
Publication date: 2023-07-21

Abstract

The application provides a method, a device, equipment and a storage medium for optimizing the picking of pickers, wherein the method comprises the following steps: acquiring the number of orders; determining the position information of each commodity in the order and the position information of the pickers; making a picking route of each picker; acquiring attribute information of each commodity in an order; combining the picking routes of all the pickers and attribute information of all the commodities to judge whether all the pickers can finish picking tasks at one time according to the picking routes; if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time; and optimizing the picking route of each picker according to the result of judging whether each picker can finish the picking task once according to the picking route, and obtaining the final route of each picker. The technical effect that this application had is: the method is used for making a picking route and improving picking efficiency.

Description

Method, device, equipment and storage medium for optimizing goods picking of goods picking personnel

Technical Field

The application relates to the technical field of order distribution and picking of electronic commerce warehouses, in particular to a method, a device, equipment and a storage medium for optimizing picking of pickers.

Background

The e-commerce warehouses that are increasingly using WMS management software are currently using pick-up for order delivery, and typically one pick-up vehicle loads several pick-up baskets, each of which can be loaded with 1 order (in some cases, one pick-up basket may also be loaded with multiple orders). Thus, a pick-up truck typically loads several orders, and the collection of orders in the truck is generally referred to as a pick batch (simply "batch").

The use of pick trucks improves the loading capacity of the cargo distributor per pick pass, but also presents a new problem: different orders need to be picked up on shelves at different positions, and a poorly aggregated batch can greatly lengthen the travel distance of a dispatcher pulling the picking truck in a warehouse. For example, a batch of 10 orders, 8 orders can be picked in the first 3 channels, but the remaining 2 orders require 15 channels to be continued for the goods to be dispensed, which results in a greatly prolonged pick effort required to complete the first 8 orders.

Accordingly, there is a need for a method, apparatus, device, and storage medium for optimizing the picking of goods by pickers for routing the goods to improve the picking efficiency.

Disclosure of Invention

The application provides a method, a device, equipment and a storage medium for optimizing picking of pickers. The method is used for improving the circuit laying efficiency and ensuring that the circuit laying is completed within a specified time.

In a first aspect, the present application provides a method of optimizing pickers for picking, for use with a computer device, the method comprising: acquiring the number of orders; determining the position information of each commodity in the order and the position information of the pickers; according to the position information of each commodity in the order and the position information of the pickers, a picking route of each picker is established; acquiring attribute information of each commodity in an order; combining the picking routes of all the pickers and the attribute information of all the commodities to judge whether all the pickers can finish picking tasks at one time according to the picking routes; if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time; and optimizing the picking route of each picker according to the result that whether each picker can finish the picking task once or not according to the picking route, and obtaining the final route of each picker.

By adopting the technical scheme, the current order quantity is acquired, the position information of each commodity in the order can be determined, then the position information of the picking personnel is acquired, a picking route is preliminarily established according to the position information of the commodity and the position information of the picking personnel, so that the picking personnel can pick a large number of commodities according to the shortest route when picking the commodities, a large amount of time is saved, and meanwhile, the picking efficiency is also ensured; and acquiring attribute information of each commodity in the order, wherein the goods can be picked up by the pickers each time, so that the pickers are required to judge whether the pickers can finish the picking task at one time according to the picking route while making the picking route, and respectively acquire the picking route of the pickers capable of finishing the picking task at one time and the picking route of the pickers failing to finish the picking task at one time, so as to optimize the route, ensure that the pickers can pick up the commodity according to the shortest route, and improve the picking efficiency.

Optionally, the acquiring the order quantity includes: when the preset interval duration is reached or the order quantity reaches the preset quantity, collecting the order to obtain the order quantity; and acquiring the order quantity.

By adopting the technical scheme, when the order is acquired, the order needs to be collected, when the preset interval duration is reached or the order quantity reaches the preset quantity, the order collection is carried out, and because the order has uncertainty, the order collection can be determined from two aspects, and the order collection is carried out in a multi-dimensional mode, so that various emergency situations can be effectively treated.

Optionally, the determining, by combining the picking route of each picker with the attribute information of each commodity, whether each picker can complete the picking task once according to the picking route includes:

the attribute information of each commodity includes: the weight information of each commodity, the volume information of each commodity and the quantity information of each commodity; obtaining the sort of the goods to be picked of each goods-picking person according to the goods-picking route of each goods-picking person; combining the picking route of each picker and the attribute information of each commodity to obtain weight information, volume information and quantity information of all the commodities to be picked of each picker; acquiring maximum weight information and maximum volume information of cargoes which can be born by the cargoes picking vehicle of each cargoes picking person; and judging whether each goods picking person can finish the goods picking task once according to the goods picking route.

Through adopting above-mentioned technical scheme, after making the goods-picking route of goods-picking personnel, acquire the attribute information of each commodity again, the attribute information of each commodity includes the weight information of each commodity, the volume information of each commodity and the quantity information of each commodity, can accurately judge whether the goods-picking personnel can accomplish the goods-picking according to the goods-picking route once, be convenient for follow-up to the adjustment of the goods-picking route of each goods-picking personnel to be convenient for each goods-picking personnel carries out the goods-picking according to the optimum route, improve goods-picking efficiency.

Optionally, after the acquiring the order quantity, the method further includes: if the order quantity exceeds a second preset quantity; grouping all orders according to preset conditions to obtain a priority order group and a non-priority order group, wherein the priority of the priority order group is higher than that of the non-priority order group; and determining ordering information of orders in each order group according to the priority of each order group after grouping.

By adopting the technical scheme, due to the fact that the orders are too much, all orders are grouped according to preset conditions, priority order processing and non-priority order processing can be obtained, the priority of the priority order processing is higher than that of the non-priority order processing, orders in the priority order processing are ordered, the acquired orders are clearly classified, the follow-up optimization of the picking route of each picker is facilitated, and accordingly picking efficiency is improved.

Optionally, after the determining whether each pick person can complete the picking task once according to the picking route, the method further includes: if all the pickers can not finish the picking task once according to the picking route; acquiring attribute information of each commodity in the order; and placing part of orders according to the attribute information of the commodities so as to enable the placed orders to be processed in a centralized manner.

By adopting the technical scheme, due to the fact that the current order is large in size or heavy in weight, all pickers cannot finish the picking task at one time according to the picking route. Therefore, the adjustment is carried out, part of special orders are placed, the placed orders are independently processed, the order picking personnel is guaranteed to pick the goods in the shortest order picking route, the order picking personnel is prevented from running for many times, and the order picking efficiency is improved.

Optionally, after placing a part of the order according to the attribute information of each commodity, the method further includes: acquiring a shelved order; matching one or more items in the placed order to a pick route of the pickers; if one or more commodities in the placed order exist on the picking route of any one or more pickers, updating the picking route of the one or more pickers to obtain a first picking route, wherein the first picking route is a route capable of completing the picking task at one time.

By adopting the technical scheme, the goods picking personnel cannot finish picking according to the picking route at one time due to overlarge volume or overlarge weight of the goods, and at the moment, part of orders need to be placed; the order is acquired again, the picking route of each picker is formulated, when the picking route of each picker is formulated again, the placed goods also participate in the new order to carry out route planning together, so that each picker can complete the picking task at one time according to the picking route, the picking plan is formulated reasonably, and the picking efficiency is improved.

Optionally, the method further comprises: acquiring the number of orders in a preset time length; drawing an order number graph according to the order number in the preset duration; predicting the order quantity in the next preset time according to the order quantity curve graph; and sending the prediction result to terminal equipment of the staff, so that the staff can make a picking plan in advance according to the prediction result.

By adopting the technical scheme, the order quantity in the preset time length is obtained, the order quantity graph is drawn according to the order quantity in the preset time length, the order quantity in the next preset time length is conveniently predicted, a corresponding adjustment plan can be made according to the prediction result, the situation that goods cannot be picked in time or a large amount of manpower is wasted due to too many orders is avoided, real-time adjustment can be made for the current order, and the applicability is strong.

In a second aspect, the present application provides a device for optimizing a pick person to pick a good, where the device includes an acquisition module, a determination module, a formulation module, a judgment module, and an optimization module; the acquisition module is used for acquiring the number of orders; acquiring attribute information of each commodity in an order; if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time; the determining module is used for determining the position information of each commodity in the order and the position information of the pickers; the formulating module is used for formulating the picking route of each picking person according to the position information of each commodity in the order and the position information of the picking person; the judging module is used for combining the picking routes of all the pickers and the attribute information of all the commodities to judge whether all the pickers can finish picking tasks at one time according to the picking routes; and the optimizing module is used for optimizing the picking route of each picker according to the result of judging whether each picker can finish the picking task at one time according to the picking route, so as to obtain the final route of each picker.

In a third aspect, the present application provides an electronic device, which adopts the following technical scheme: the method comprises a processor, a memory, a user interface and a network interface, wherein the memory is used for storing instructions, the user interface and the network interface are used for communicating with other devices, and the processor is used for executing the instructions stored in the memory so as to enable the electronic device to execute a computer program of any interview matching degree judging method.

In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical solutions: a computer program capable of being loaded by a processor and executing any one of the above-described interview matching degree determination methods is stored.

In summary, the present application includes at least one of the following beneficial technical effects:

1. the method comprises the steps of respectively obtaining a picking route of a picker capable of completing a picking task at one time and a picking route of a picker incapable of completing the picking task at one time, optimizing the routes, ensuring that each picker can pick according to the shortest route, and improving the picking efficiency;

2. according to the order quantity in the preset duration, an order quantity graph is drawn, the order quantity in the next preset duration is conveniently predicted, a corresponding adjustment plan can be made according to a prediction result, the situation that goods cannot be picked in time due to excessive orders or a large amount of manpower is wasted due to the fact that the orders are too few is avoided, real-time adjustment can be made for the current order, and applicability is high.

Drawings

FIG. 1 is a flow chart of a method of optimizing pickers' picking in accordance with an embodiment of the present application;

FIG. 2 is a schematic diagram of an optimized pickers picking configuration according to embodiments of the present application;

fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Reference numerals illustrate: 1. an acquisition module; 2. a determining module; 3. making a module; 4. a judging module; 5. an optimization module; 1000. an electronic device; 1001. a processor; 1002. a communication bus; 1003. a user interface; 1004. a network interface; 1005. a memory.

Detailed Description

In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.

In the description of embodiments of the present application, words such as "exemplary," "such as" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "illustrative," "such as" or "for example" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "illustratively," "such as" or "for example," etc., is intended to present related concepts in a concrete fashion.

Fig. 1 is a flow chart of a method for optimizing pickers to pick in accordance with an embodiment of the present application. It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows; the steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders; and at least some of the steps in fig. 1 may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the sub-steps or stages are performed necessarily occur in sequence, but may be performed alternately or alternately with at least some of the other steps or sub-steps of other steps.

The application discloses a method for optimizing the picking of pickers, as shown in fig. 1, which comprises S1-S5.

S1, acquiring the number of orders, and determining the position information of each commodity in the orders and the position information of the pickers.

In one example, the merchandise is purchased as the user is placed at any time, and the amount of the placement may vary due to the dimensions of time, season, holiday, etc. Therefore, to facilitate management of the orders of the user, the order quantity, that is, the order collection, needs to be acquired regularly or quantitatively. After the order is collected, the placement positions of all commodities and the positions of all pickers need to be determined. Each commodity has a corresponding placement position, and can be directly obtained, and the positions of the pickers can be obtained in real time by obtaining the communication equipment of all pickers.

When the preset interval duration is reached or the order quantity reaches the preset quantity, collecting the order to obtain the order quantity; the order quantity is acquired.

In one example, the collection list can be based on time and number, and the preset interval duration can be half an hour, and the collection list is carried out every half an hour; the number of orders can also be used as a basis, and the number of orders in different time periods can be different due to the reasons of existence time, seasons, holidays and the like or the number of orders is increased due to special holidays. Therefore, the preset number can be one thousand by setting the preset number, and when the order number reaches one thousand, the order collection is performed. After the orders are collected, each order is refined, and the order quantity is obtained.

If the number of orders exceeds the second preset number; grouping all orders according to preset conditions to obtain a priority order group and a non-priority order group, wherein the priority of the priority order group is higher than that of the non-priority order group; and determining ordering information of orders in each order group according to the priority of each order group after grouping.

In one example, the second preset number may be five hundred, and if the number of the current orders exceeds five hundred, the orders are classified, and the classification criteria are many, for example, a cargo owner, a carrier, a warehouse area, etc., and may be set by themselves according to the actual situation. Taking a warehouse area and a picker as an example, sorting commodities by using the positions of the pickers, wherein the commodities of five shelves closest to the pickers in the orders are a group, namely a priority order group, and the rest orders are non-priority groups, then sorting the orders in the priority order group and the non-priority order group according to the distance between each commodity and the pickers, wherein the orders in the priority order group can be preferentially picked, and when picking, making a picking route according to the order sorting of the priority order group.

S2, according to the position information of each commodity in the order and the position information of the pickers, a picking route and a picking task of each picker are formulated.

In one example, in order to quickly pick and make each pick person pick in the shortest path on the premise of knowing the position of each order and the position of each pick person, a pick task is allocated to each pick person, a pick route is formulated according to the pick task, different pick tasks are allocated based on the position of each pick person, and it is noted that the pick tasks of the unnecessary pick person may be different and mainly determined according to the number of orders, the position of each order and the position of each pick person.

S3, acquiring attribute information of each commodity in the order; and combining the picking routes of all the pickers and attribute information of all the commodities to judge whether all the pickers can finish picking tasks at one time according to the picking routes.

In one example, attribute information for each item in the order is obtained, and there are a plurality of items of attribute information, such as the number of items ordered by the user, the size of each item, the weight of each item, the carrier and inventory of the item, and so on. The commodity attributes may include a plurality of attributes, depending on the particular situation. And then judging whether each goods picking person can finish the goods picking task once according to the goods picking route. For example, each picker is provided with a picker for picking, and there are cases where picking cannot be completed at one time according to a picking route because of limited goods that can be picked by the picker. It may be impossible to complete the picking at one time due to excessive volume or weight of the goods. For example, a person may be a hundred computers and other items to be picked, and the limited capacity of the picking truck may result in the person not completing the picking route at a time according to the picking route.

The attribute information of each commodity includes: weight information of each commodity, volume information of each commodity and quantity information of each commodity; obtaining the types of goods to be picked of all the pickers according to the picking routes of all the pickers; combining the picking route of each picker and the attribute information of each commodity to obtain weight information, volume information and quantity information of all the commodities to be picked of each picker; acquiring maximum weight information and maximum volume information of cargoes which can be born by a cargoes picking vehicle of each cargoes picking person; and judging whether each goods picking person can finish the goods picking task once according to the goods picking route.

In one example, the attribute information of each commodity includes: weight information of each commodity, volume information of each commodity, and quantity information of each commodity. When the order picking route is firstly collected and then determined, the volume of the commodities is not considered, only the shortest route or the optimal route is considered, and the differences of the quantity, the volume, the weight and the like of the commodities exist, so that the route is optimized again by combining the attribute and the route of the commodities. Each goods-picking person is provided with a goods-picking truck, the maximum weight and the maximum volume which can be borne by the goods-picking truck are the maximum weight and the maximum volume which can be picked by the goods-picking person, and the basic information of the goods-picking truck of each goods-picking person is obtained to judge whether each goods-picking person can finish the goods-picking task at one time according to the goods-picking route.

And S4, if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers who complete the picking task at one time.

In one example, there is a sort job that the sort personnel fails to complete at a time according to the sort route, and there is a sort job that the sort personnel can complete at a time according to the sort route, and a sort route of the sort personnel that can complete the sort job is obtained.

And S5, optimizing the picking route of each picker according to the result of judging whether each picker can finish the picking task once according to the picking route, and obtaining the final route of each picker.

In one example, pick results are obtained for each individual picker and adjusted to each other. For example, there are a pickers a and B pickers, since the a pickers fail to complete the pickers at one time according to the pickers ' routes, while the B pickers complete the pickers ' tasks while the pickers ' carts have a remaining space, and the B pickers ' routes are similar to the a pickers ' routes, the a pickers ' rated routes and pickers ' tasks, and the B pickers ' routes and pickers ' tasks may be adjusted. It should be noted that, when the picking route and the picking task of the A and the B are adjusted, other pickers can be adjusted to assist according to specific situations, if the picking task is still not completed, part of the commodities can be placed, and the placed commodities and the commodities of the next wave are subjected to task allocation and adjustment of the next round.

If all the pickers can not finish the picking task at one time according to the picking route; acquiring attribute information of each commodity in the order; and placing part of orders according to the attribute information of each commodity so as to enable the placed orders to be processed in a centralized way.

In one example, when all pickers cannot complete the picking task at a time according to the picking route, attribute information of each item is acquired, and a part of the order may be selected to be placed first. For example, currently, each pick person cannot complete the pick task at one time due to the limited pick weight of the pick truck and the limited capacity of the truck, at which time a portion of the order may be placed and later will be centrally processed by the placed order. The pick personnel completes one pick according to the pick route, and then the placed order and other commodities can participate in pick distribution again until the placed order is processed.

Acquiring a shelved order; matching one or more items in the placed order to the pick route of the pickers; if one or more commodities in the placed order exist on the picking route of any one or more pickers, updating the picking route of the one or more pickers to obtain a first picking route, wherein the first picking route is a route capable of completing the picking task at one time.

In one example, a placed order is acquired, there may be various special reasons that the order is placed, and the placed order may be one or more. Since the system is constantly collecting orders and then assigning tasks to individual pickers, the placed orders can participate in the collection of orders at any time and then in the assignment tasks. For example, in the first dispense, since the product C is oversized and requires a picker to pick up C one hundred pieces, and one picker picks up twenty pieces at a time, the remaining eighty pieces are required to rest; when the task allocation and the goods picking route are formulated at any time, if the goods C correspond to the goods picking route of any goods picking person, on the premise that the goods picking person can finish the personal goods picking task, part of the goods C are picked according to actual conditions. Of course, the goods picking device can also be adjusted according to the goods picking tasks of all goods picking personnel, so that goods picking can be performed according to the shortest route, and all goods can be picked completely.

Acquiring the number of orders in a preset time length; drawing an order number graph according to the order number in the preset duration; predicting the number of orders in the next preset time according to the order number graph; and sending the prediction result to terminal equipment of the staff, so that the staff can make a picking plan in advance according to the prediction result.

In one example, the number of orders in a preset time period is obtained, the preset time period can be one day, the total singular number of orders in each time period in one day is obtained, and the number of orders in each time period is drawn into a graph, the graph is displayed through a visual interface, the number of orders in each next preset time period can be obtained through the graph, the trend of the orders can be clearly obtained through the graph, and then a worker can make appropriate adjustment according to the graph. For example, if it is currently known through the graph that the order quantity will suddenly increase at two pm points each day, at this time, the pick-up personnel may be added at two pm points each day to cope with the situation, and the actual situation is mainly the actual situation, and the excessive description will not be made here.

Based on the method, the embodiment of the application also discloses a schematic diagram of the line-optimized picking personnel picking structure.

As shown in fig. 2, an apparatus for optimizing the picking of a person for picking, the apparatus comprising: the system comprises an acquisition module 1, a determination module 2, a formulation module 3, a judgment module 4 and an optimization module 5;

the acquisition module 1 is used for acquiring the number of orders; acquiring attribute information of each commodity in an order; if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time; the determining module 2 is used for determining the position information of each commodity in the order and the position information of the pickers; the making module 3 is used for making a picking route of each picker according to the position information of each commodity in the order and the position information of the picker; the judging module 4 is used for combining the picking route of each picker and attribute information of each commodity to judge whether each picker can finish the picking task once according to the picking route; the optimizing module 5 is used for optimizing the picking route of each picker according to the result of judging whether each picker can complete the picking task once according to the picking route, and obtaining the final route of each picker.

It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.

Referring to fig. 3, a schematic structural diagram of an electronic device is provided in an embodiment of the present application. As shown in fig. 3, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, at least one communication bus 1002.

Wherein the communication bus 1002 is used to enable connected communication between these components.

The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may further include a standard wired interface and a wireless interface.

The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.

Wherein the processor 1001 may include one or more processing cores. The processor 1001 connects various parts within the entire server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Alternatively, the processor 1001 may be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 1001 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 1001 and may be implemented by a single chip.

The Memory 1005 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). The memory 1005 may be used to store instructions, programs, code, sets of codes, or sets of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described respective method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 1005 may also optionally be at least one storage device located remotely from the processor 1001. As shown in FIG. 3, an operating system, network communication module, user interface module, and an application program for a method of optimizing pickers may be included in memory 1005, which is a computer storage medium.

In the electronic device 1000 shown in fig. 3, the user interface 1003 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 1001 may be configured to invoke an application in the memory 1005 that stores a method of optimizing pickers for pick, which when executed by one or more processors, causes the electronic device to perform the method as described in one or more of the embodiments above.

An electronic device readable storage medium storing instructions. When executed by one or more processors, cause an electronic device to perform the method as described in one or more of the embodiments above.

It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.

In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as the division of the units, merely a logical function division, and there may be additional manners of dividing the actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.

The foregoing is merely exemplary embodiments of the present disclosure and is not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.

Claims

1. A method of optimizing pickers' picking for use with a computer device, the method comprising:

acquiring the number of orders;

determining the position information of each commodity in the order and the position information of the pickers;

according to the position information of each commodity in the order and the position information of the pickers, a picking route and a picking task of each picker are formulated;

acquiring attribute information of each commodity in an order;

combining the picking routes of all the pickers and the attribute information of all the commodities to judge whether all the pickers can finish picking tasks at one time according to the picking routes;

if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time;

and optimizing the picking route of each picker according to the result that whether each picker can finish the picking task once or not according to the picking route, and obtaining the final route of each picker.

2. The method of optimizing pickers' picking of claim 1, wherein the acquiring the order quantity includes:

when the preset interval duration is reached or the order quantity reaches the preset quantity, collecting the order to obtain the order quantity;

and acquiring the order quantity.

3. The method for optimizing picking by pickers according to claim 1, wherein the step of combining the picking route of each picker with the attribute information of each commodity to determine whether each picker can complete the picking task once according to the picking route comprises:

the attribute information of each commodity includes: the weight information of each commodity, the volume information of each commodity and the quantity information of each commodity;

obtaining the sort of the goods to be picked of each goods-picking person according to the goods-picking route of each goods-picking person;

combining the picking route of each picker and the attribute information of each commodity to obtain weight information, volume information and quantity information of all the commodities to be picked of each picker;

acquiring maximum weight information and maximum volume information of cargoes which can be born by the cargoes picking vehicle of each cargoes picking person;

and judging whether each goods picking person can finish the goods picking task once according to the goods picking route.

4. The method of optimizing pickers' picking of claim 1, further comprising, after the acquiring the order quantity:

if the order quantity exceeds a second preset quantity;

grouping all orders according to preset conditions to obtain a priority order group and a non-priority order group, wherein the priority of the priority order group is higher than that of the non-priority order group;

and determining ordering information of orders in each order group according to the priority of each order group after grouping.

5. The method of claim 1, wherein said determining whether each of said pickers can complete a pick job once according to said pick route further comprises:

if all the pickers can not finish the picking task once according to the picking route;

acquiring attribute information of each commodity in the order;

and placing part of orders according to the attribute information of the commodities so as to enable the placed orders to be processed in a centralized manner.

6. The method of claim 5, wherein after placing a portion of the order according to the attribute information of each item, further comprising:

acquiring a shelved order;

matching one or more items in the placed order to a pick route of the pickers;

if one or more commodities in the placed order exist on the picking route of any one or more pickers, updating the picking route of the one or more pickers to obtain a first picking route, wherein the first picking route is a route capable of completing the picking task at one time.

7. A method of optimizing pickers' picking as set forth in claim 1, further comprising:

acquiring the number of orders in a preset time length;

drawing an order number graph according to the order number in the preset duration;

predicting the order quantity in the next preset time according to the order quantity curve graph;

and sending the prediction result to terminal equipment of the staff, so that the staff can make a picking plan in advance according to the prediction result.

8. An apparatus for optimizing the picking of a person picking, the apparatus comprising: the system comprises an acquisition module (1), a determination module (2), a formulation module (3), a judgment module (4) and an optimization module (5);

the acquisition module (1) is used for acquiring the number of orders; acquiring attribute information of each commodity in an order; if one or more pickers cannot complete the picking task at one time, acquiring a picking route of the pickers completing the picking task at one time;

the determining module (2) is used for determining the position information of each commodity in the order and the position information of the pickers;

the formulating module (3) is used for formulating a picking route of each picker according to the position information of each commodity in the order and the position information of the picker;

the judging module (4) is used for combining the picking route of each picker and the attribute information of each commodity to judge whether each picker can finish the picking task once according to the picking route;

and the optimizing module (5) is used for optimizing the picking route of each picking person according to the result of judging whether each picking person can finish the picking task at one time according to the picking route, and obtaining the final route of each picking person.

9. An electronic device comprising a processor (1001), a memory (1005), a user interface (1003) and a network interface (1004), the memory (1005) being configured to store instructions, the user interface (1003) and the network interface (1004) being configured to communicate to other devices, the processor (1001) being configured to execute the instructions stored in the memory to cause the electronic device (1000) to perform the method according to any one of claims 1-7.

10. A computer readable storage medium, characterized in that a computer program is stored which can be loaded by a processor and which performs the method according to any of claims 1-7.